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'''Introduction'''
Mozilla’s history is steeped in openness and transparency - it’s simply core to what we do and how we see ourselves in the world. We are always looking for ways to bring our mission to life in ways that help create a healthy internet and support the Mozilla Manifesto. One of our commitments says “We are committed to an internet that elevates critical thinking, reasoned argument, shared knowledge, and verifiable facts”.
To this end, we have spent a good amount of time considering how we can publicly share our Mozilla telemetry data sets - it is one of the most simple and effective ways we can enable collaboration and share knowledge. But, only if it can be done safely and in a privacy protecting, principled way. We believe we’ve designed a way to do this and we are excited to outline our approach here.
'''Dataset Publishing Process'''
We want our data publishing review process, as well as our review decisions to be public and understandable, similar to our Mozilla Data Collection program. To that end, our full dataset publishing policy and details about what considerations we look at before determining what is safe to publish can be found below, including asummary of the critical pieces of that process.
* What metrics are sensitive, and at which level
* How we characterize the levels of aggregation
'''
How we characterize the levels of aggregation'''
The table below describes the various types of aggregation levels we are defining.
{| class="wikitable"
|-
! Level !! Aggregation !! Examples
|-
| 1 || Statistical / ML Models A model built/trained using real data || TAAR, Federated learning models, Forecasting models
|-
| Example || Example || Example
|-
| Example || Example || Example
|}
